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Drift Detection

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Showing 51–100 of 181 papers

TitleStatusHype
Fault Detection and Monitoring using a Data-Driven Information-Based Strategy: Method, Theory, and Application—0
How to Sustainably Monitor ML-Enabled Systems? Accuracy and Energy Efficiency Tradeoffs in Concept Drift Detection—0
Open-Source Drift Detection Tools in Action: Insights from Two Use Cases—0
Anomaly Detection for Incident Response at Scale—0
Hybrid Ensemble-Based Travel Mode Prediction—0
Unsupervised Concept Drift Detection based on Parallel Activations of Neural NetworkCode0
On Extending the Automatic Test Markup Language (ATML) for Machine Learning—0
Incremental Learning with Concept Drift Detection and Prototype-based Embeddings for Graph Stream Classification—0
An incremental hybrid adaptive network-based IDS in Software Defined Networks to detect stealth attacks—0
Unveiling Group-Specific Distributed Concept Drift: A Fairness Imperative in Federated LearningCode0
Estimating Model Performance Under Covariate Shift Without Labels—0
Investigating the Suitability of Concept Drift Detection for Detecting Leakages in Water Distribution NetworksCode0
Explainable Adaptive Tree-based Model Selection for Time Series Forecasting—0
METER: A Dynamic Concept Adaptation Framework for Online Anomaly Detection—0
A Conditioned Unsupervised Regression Framework Attuned to the Dynamic Nature of Data StreamsCode0
An Empirical Study of Uncertainty Estimation Techniques for Detecting Drift in Data Streams—0
One or Two Things We know about Concept Drift -- A Survey on Monitoring Evolving Environments—0
Data Drift Monitoring for Log Anomaly Detection Pipelines—0
EdgeFD: An Edge-Friendly Drift-Aware Fault Diagnosis System for Industrial IoT—0
Cost-Effective Retraining of Machine Learning Models—0
Balancing Computational Efficiency and Forecast Error in Machine Learning-based Time-Series Forecasting: Insights from Live Experiments on Meteorological Nowcasting—0
Efficient Concept Drift Handling for Batch Android Malware Detection ModelsCode0
Detecting covariate drift in text data using document embeddings and dimensionality reductionCode0
AIDPS:Adaptive Intrusion Detection and Prevention System for Underwater Acoustic Sensor Networks—0
Uncovering Drift in Textual Data: An Unsupervised Method for Detecting and Mitigating Drift in Machine Learning Models—0
Drifter: Efficient Online Feature Monitoring for Improved Data Integrity in Large-Scale Recommendation Systems—0
Adapting to Change: Robust Counterfactual Explanations in Dynamic Data LandscapesCode0
An efficient and straightforward online quantization method for a data stream through remove-birth updatingCode0
iPDP: On Partial Dependence Plots in Dynamic Modeling ScenariosCode0
Reliable and Interpretable Drift Detection in Streams of Short Texts—0
OPTWIN: Drift identification with optimal sub-windows—0
Autoencoder-based Anomaly Detection in Streaming Data with Incremental Learning and Concept Drift Adaptation—0
Measuring Rule-based LTLf Process Specifications: A Probabilistic Data-driven ApproachCode0
Advances on Concept Drift Detection in Regression Tasks using Social Networks Theory—0
Always Strengthen Your Strengths: A Drift-Aware Incremental Learning Framework for CTR Prediction—0
Towards Computational Performance Engineering for Unsupervised Concept Drift Detection -- Complexities, Benchmarking, Performance AnalysisCode0
CADM: Confusion Model-based Detection Method for Real-drift in Chunk Data Stream—0
Unsupervised Detection of Behavioural Drifts with Dynamic Clustering and Trajectory AnalysisCode0
Feature Relevance Analysis to Explain Concept Drift -- A Case Study in Human Activity Recognition—0
A Sequential Concept Drift Detection Method for On-Device Learning on Low-End Edge Devices—0
On the Change of Decision Boundaries and Loss in Learning with Concept Drift—0
Are Concept Drift Detectors Reliable Alarming Systems? -- A Comparative Study—0
Unsupervised Unlearning of Concept Drift with AutoencodersCode0
Targeted Attention for Generalized- and Zero-Shot Learning—0
A monitoring framework for deployed machine learning models with supply chain examples—0
Demo: LE3D: A Privacy-preserving Lightweight Data Drift Detection Framework—0
LE3D: A Lightweight Ensemble Framework of Data Drift Detectors for Resource-Constrained Devices—0
A Hybrid Active-Passive Approach to Imbalanced Nonstationary Data Stream Classification—0
A Model Drift Detection and Adaptation Framework for 5G Core Networks—0
Detecting Concept Drift in the Presence of Sparsity -- A Case Study of Automated Change Risk Assessment System—0
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